iron-regulated proteome and transcriptome of neisseria meningitidis

Iron-regulatedproteome and transcriptome

of Neisseria meningitidis

M. BASLER, I. LINHARTOVÁ, P. HALADA,J. NOVOTNÁ, S. BEZOUŠKOVÁ, R. OSIČKA,

J. WEISER, J. VOHRADSKÝ and P. ŠEBO

Institute of Microbiology of the Czech Academy of Sciences, Prague

IRON HOMEOSTASIS

Iron is essential to virtually all organisms, but poses problems of toxicity and poor solubility

Basic principles of iron homeostasis• There are essentially 5 strategies used by bacteria in the

management of iron:1)High-affinity iron transport enabling iron to be scavenged, in

various forms, from the surroundings.

2)Deposition of intracellular iron stores to provide a source of iron that can be drawn upon when external supplies are limited.

3)Employment of redox stress resistance systems (e.g. degradation of iron-induced reactive oxygen species and repair of redox stress-induced damage).

4)Control of iron consumption by down-regulating the expression of iron-containing proteins under iron-restricted conditions.

5)An over-arching iron-responsive regulatory system that co-ordinates the expression of the above iron homeostatic machinery according to iron availability.

Mechanism of Fur regulation

Andrews – FEMS Microbiology Reviews 27 (2003); Delany – Mol Microbiol 52 (2004)

High iron Low iron

NADH dehydrogenase subunits


ON OFF

iron-responsive repression of gene transcriptionHowever, recently also iron-responsive activation of gene transcription was discovered

Gene expression in N. meningitidisunder iron starvation

• In human body more than 99,9% of iron is bound to transport (transferrin, lactoferrin) and storage proteins (ferritin, heme-containing compounds)

• For invasion and proliferation bacteria need to induce specific pathways capable of scavenging iron from the host

• Low iron concentration tells the pathogen it is inside the host

• Several Neisseria virulence genes are iron-regulated

Neisseria meningitidisObligate human commensal gram-negative bacterium colonizing the nasopharynx of about 10% of healthy subjects.

Risk factors:upper respiratory infection, immunodeficiency, age

Risk groups:military recruits, refugees, contacts of patients

Treatment (7 to 14 days):intravenous penicillin or cephalosporins, chloramphenicol

Vaccine:purified polysaccharidesserogroups A, C, Y and W-135

lactoferrin

ferritintransferrin

hemoglobin

2 µM iron

Neisseria meningitidis – life cycle Iron availability in the human host

Experimental design – iron starvation

7 µM Fe(NO3)3

10 h

RNAmicroarray

Proteins2-D + MS

O/NRPMI2 h

100 µM Desferal10 h

RNAmicroarray

Proteins2-D + MS

Iron regulated

PROTEOMEI. LINHARTOVÁ, P. HALADA,

J. NOVOTNÁ, S. BEZOUŠKOVÁ, J. VOHRADSKÝ

+ Fe(NO3)3 + Desferal Image and data analysis

Mass Spectrometry

theor. 788 proteins theor. 962 proteins

4 7 6 11pI pI100

5

100

15

kDa kDa

DF set – 6 gelsFe set – 7 gels

362 protein spots analyzed46 spots in DF set31 spots in Fe set

DF set – 8 gelsFe set – 10 gels

238 protein spots analyzed67 spots in DF set11 spots in Fe set

114 spots were identified by MS64 unique proteins in DF set27 unique proteins in Fe set

Iron regulated

TRANSCRIPTOMEM. BASLER, I. LINHARTOVÁ

Cy3Cy5

Probe

Target: PCR products

Hybridization

Chip

+

Image processing

Data mining and visualization

+ Fe(NO3)3 + Desferal

N. meningitidis whole genome slide (Eurogentec) - 2194 ORFs

3 biological experiments8 whole genome slides

62 genes up-regulated in DF64 genes up-regulated in Fe

[email protected]@biomed.cas.cz

DATA ANALYSIS

scanning, image analysis, quality control, background subtraction,

normalization, data mining

Microarray Data Flow

Database

AGED

Database

Others…

Database

MAD

Raw Gene Expression Data

Normalized Data with Gene Annotation

Interpretation of Analysis Results

.tiff Image File

Gene Annotation

ScannerPrinter

Image Analysis

Normalization / Filtering

Expression Analysis

Scanning

Image analysisquality control

background subtraction

SpotFinderwww.tigr.org

Basic Steps from Image to Table

1. Image File Loading

2. Construct or Apply an Overlay Grid

3. ComputationsFind Spot Boundary and Area

Intensity Calculation

Background Calculation and Correction

4. Quality Control

5. Text File Output

Applying an Overlay Grid

• What does it accomplish?–The grid cells set a boundary for the spot finding algorithms.–The grid cells also define an area for background correction.

Area inside contour is used for spot intensity calculation

Area outside contour is used for local background calculation

Reported “Intensity” = Integral – BKG * A

NormalizationData mining, filtering

MIDASwww.tigr.org

Rwww.r-project.org

Why is normalization important?• There are many sources of experimental variation:

During preparation – mRNA extraction, labeling

During manufacture of array – amount of spotted DNA

During hybridization – amount of sample applied, amount of target hybridized

After hybridization – optical measurements, label intensity, scanner

• Proper normalization is needed before ratios from different chips are compared!

4.5 5.0 5.5 6.0 6.5

-20

24

68

Intensity vs. expression ratio slide #6

Mean of Log10 intensities for both channels

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Histogram of expression ratios normalized data - slide #6

5146 spots

De

nsi

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-3 -2 -1 0 1 2 3

0.0

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0.4

0.6

0.8

1.0

Data mining

• Visualization and control (R)

• Filtering (MS Excel, R)One sample t-test

• mean of Log2 ratios for all replicates• mean is not equal to 0• p-val < 0.01

Expression ratio > 1.7x

• Clustering

• KEGG GENES Database

• PubMed

Distribution of intensity ratios for each gene

Finding Significant Genes by t-test

Average ratio is same

Not significantp-val > 0.01

Significantp-val < 0.01

RESULTS

Complementarity of proteome and transcriptome

199 genes regulated by iron

114 genes up-regulated in low iron85 genes up-regulated in high iron

73 18 108

91 genes found in

proteome126 genes found in

transcriptome

Identification of iron-activated and repressed Fur-dependent genes by transcriptome analysis of

Neisseria meningitidis group B Grifantini et al., PNAS, August 5, 2003

• After iron addition to an iron-depleted bacterial culture 153 genes were up-regulated and 80 were down-regulated

• Only 50% of the iron-regulated genes were found to contain Fur-binding consensus sequences in their promoter regions.

• Different growth conditions. N. meningitidis MC58 cultures were grown in chemically defined medium with 12.5 µM desferal (iron-depleted) for 3 h. After this adaptation to iron starvation, half of the culture was supplemented with 100 µM ferric nitrate, and growth continued for a 5-h period.

Overlap of PNAS and our data

• PNAS data are for N. m. B

• NMB to NMA conversion tableblastall -p blastp -d Nm_Z2491 -b1 -m8 -i MC58.txt -o NmB_in_NmA.txt

85 genes found in

proteome+ 1 not similar to NmA or NmB

117 genes found in

transcriptome

191 genes found by Siena group+ 40 not on EGT chip, + 4 more than once

62 1 77

245 (2)15

145

Correlation between our data and PNAS data39 genes

R2 = 0.7568

-4

-3

-2

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Our data (Log2 expression ratio)

PN

AS

da

ta (

Lo

g2

exp

res

sio

n r

ati

o)

Conclusions for combined results

• There is more iron-regulated genes than expected! Up to about 300.

• In a single type of experiment we and the Siena group found 10x more genes regulated by iron concentration than before the entire scientific community in 40 years!

Some what came out …

IRON HOMEOSTASIS

Iron is essential to virtually all organisms, but poses problems of toxicity and poor solubility

Basic principles of iron homeostasis• There are essentially 5 strategies used by bacteria in the

management of iron:1)High-affinity iron transport enabling iron to be scavenged, in

various forms, from the surroundings.

2)Deposition of intracellular iron stores to provide a source of iron that can be drawn upon when external supplies are limited.

3)Employment of redox stress resistance systems (e.g. degradation of iron-induced reactive oxygen species and repair of redox stress-induced damage).

4)Control of iron consumption by down-regulating the expression of iron-containing proteins under iron-restricted conditions.

5)An over-arching iron-responsive regulatory system that co-ordinates the expression of the above iron homeostatic machinery according to iron availability.

I.TRANSPORT OF IRON

High-affinity iron transport systems allowing acquisition in various forms from the environment

are vital to all commensal and pathogenic bacteria

lactoferrin

ferritintransferrin

hemoglobin

2 µM iron

Iron sources in the human host

Iron acquisition mechanisms• Siderophore mediated

N. meningitidis utilize heterologous siderophores

• Receptor mediatedTransferrin and lactoferrin receptors

Hemoglobin receptor

Haptoglobin-hemoglobin receptor

• Siderophores and hemophores are taken into the cell whole.

• Host carrier proteins are not transported into the cell. Iron and heme must be stripped away prior to transport.

7x

These results validate the experimental procedure!

5x

3x

5x

4x

3x

5x - LbpB

4x - LbpA

Iron acquisition system is up-regulated in low iron

Proteins up-regulated in low iron

Other iron acquisition system?

Method Reg Protein Name

Arrays 3.13 possible periplasmic protein

Arrays 6.50 putative integral membrane protein

Arrays 2.55 putative integral membrane protein

Arrays 1.91 putative membrane protein

Arrays 3.24 putative lipoprotein

Arrays 5.50 putative periplasmic protein


Proteome 2.35 putative periplasmic protein

Arrays 1.87putative periplasmic hypothetical protein

Basic periplasmic proteins up in low iron

Protein name Reg MW pI

putative periplasmic protein -5.50 16427.6 11.0

putative periplasmic protein -5.24 31673.7 9.9

hypothetical protein NMA1073 -3.14 19533.4 10.9

major ferric iron binding protein -2.79 35841.9 10.2

Other periplasmic transporters?

II.REGULATORY SYSTEMS

An over-arching iron-responsive regulatory system thatco-ordinates the expression of the iron homeostatic machinery

according to iron availability is the Fur system

Mechanism of Fur regulation

Andrews – FEMS Microbiology Reviews 27 (2003); Delany – Mol Microbiol 52 (2004)

High iron Low iron



ON OFF

iron-responsive repression of gene transcriptionHowever, recently also iron-responsive activation of gene transcription was discovered

Transcriptional regulators possibly involved regulation of iron homeostasis

Method +/- Reg Protein Name

Both DF 2.15 ferric uptake regulation protein

Arrays DF 2.68 putative transcriptional regulator

Arrays DF 2.02 putative transcriptional regulator

Proteome DF only DNA-binding response regulator

Proteome DF only Integration host factor alpha-subunit (IHF-alpha)

Arrays Fe 2.28 AsnC-family transcriptional regulator

Arrays Fe 2.53 putative transcriptional regulator

Arrays Fe 1.93 putative ATP-dependent RNA helicase

Arrays Fe 1.79 ribonuclease PH

Grifantini – PNAS, 2003; V. Scarlato (2003, J Bact) – Fur is autoregulated in Neisseria meningitidis

Iron can regulate gene expression in a Fur-independent manner for approx. 50 % of the up/down regulated genes.

• The generally accepted concept that iron homeostasis in bacteria is regulated by Fur may be an oversimplification.

• Is there a hierarchy of iron-dependent regulation by a cascade of transcriptional activators and/or repressors?

Transcriptional regulators possibly involved regulation of iron homeostasis

Masse – PNAS, 2002

Positive regulation by Fur in E. coliA small non-coding RNA (RyhB) acts as a Fur repressed negative

regulator of genes induced in presence of iron in E. coli.

III.IRON STORAGE

Deposition of intracellular iron in stores offers a source of iron that can be used when external supplies are limited

Proteins involved in iron storage• Free iron in presence of oxygen can form free

radicals which are toxic to the cell.• Storage of iron in nontoxic form is very important!• Two types of iron storage proteins have been

identified in bacteria:bacterioferritin - heme iron and nonheme ironferritin - only iron and not heme

• In presence of ironbfrA - up-regulated more than 11 timesbfrB - up-regulated nearly 8 times

• In presence of desferalputative ferredoxin - up-regulated 2.4 times

Andrews – FEMS Microbiology Reviews 27 (2003)

Bfr500 kDa, 2000-3000 iron atoms/24-mer

Dps250 kDa, 500 iron atoms/12-mer

Structures of iron storage proteins from E. coli

IV.IRON CONSUMPTIONControl of iron consumption by down-regulating the expression of iron-containing proteins under iron-

restricted conditions

CITRATE CYCLE

Fe

DF

The overlap of proteome and transcriptome data shows that

FumC substitutes for FumA during iron starvation

• In presence of iron– Neisseria express iron containing (Fe-S)fumarate hydratase class I (FumA)– up-regulated almost 2 times on level of RNA and FumA protein was found only in Fe set of gels.

• In presence of desferal– Neisseria express “iron free” isoenzymefumarate hydratase class II (FumC)– up-regulated almost 4 times on level of RNA and FumC protein was found only in DF set of gels.

Park – Journal of bacteriology, 1995

PROTEOSYNTHESIS

Proteins up-regulated in iron


Arrays 1.73 30S ribosomal protein S18

Arrays 1.83 30S ribosomal protein S6

Arrays 1.80 50S ribosomal protein L27

Arrays 1.90 50S ribosomal protein L31

Arrays 1.82 putative additional 50S ribosomal protein L31

Proteome only 50S ribosomal protein L4

Proteome 2.06 50S ribosomal protein L9

Proteome 2.13 elongation factor G (EF-G)

Proteome only hypothetical protein NMA1094*

Proteome only translation elongation factor Tu

*Protein NMA1094 was annotated by TIGR as ribosomal 5S rRNA E-loop binding protein Ctc/L25/TL5

HYPOTHETICAL PROTEINS


Proteome only conserved hypothetical protein

Proteome only hypothetical protein NMA1013

Arrays 7.89 hypothetical protein NMA0957





Arrays 2.92 hypothetical protein


Proteome 2.19 conserved hypothetical protein















Hypothetical proteins up in low iron

Hypothetical proteins up in high ironMethod Reg Protein Name










Arrays 1.90 hypothetical periplasmic protein

Arrays 1.87 outer membrane protein



Arrays 1.78putative periplasmic binding protein


SUMMARY

Genes up-regulated at low-iron conditions 114 genes

• Transport and binding proteins

transferrin and lactoferrin binding proteins

TonB protein

siderophore receptor

ferric binding protein

ABC transporter

• Virulence factorspilins

opaD

• Transcriptional regulatorsferric uptake regulation protein

integration host factor (IHF)

hypothetical DNA binding proteins

putative regulators

• 15 putative membrane and periplasmic proteins

• 30 hypothetical proteins

Genes up-regulated at high-iron conditions 85 genes

• Iron storagebacterioferritins

• Energy metabolismelectron transport

• cytochromes

• NADH dehydrogenase

TCA cycle• fumarate hydratase

• aconitate hydratase

• citrate synthase

• Protein synthesisribosomal proteins

translation and elongation factors

• Transcriptional regulatorsAsnC-family transcriptional regulatorDNA binding proteinsputative regulatorsribonuclease

• 15 hypothetical proteins

Acknowledgments

Sponsors:AV ČRMBÚ AV ČRHHMI

Irena Linhartová

Petr Halada

Jana Novotná

Silvia Bezoušková

Jiří Vohradský

Radim Osička

Jaroslav Weiser

Peter Šebo

iron-regulated proteome and transcriptome of neisseria meningitidis

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